
'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


lowerCAmelCase					:    Dict           = {
    'configuration_encodec': [
        'ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'EncodecConfig',
    ],
    'feature_extraction_encodec': ['EncodecFeatureExtractor'],
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCAmelCase					:    List[Any]           = [
						    'ENCODEC_PRETRAINED_MODEL_ARCHIVE_LIST',
						    'EncodecModel',
						    'EncodecPreTrainedModel',
						]

if TYPE_CHECKING:
						from .configuration_encodec import (
						    ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP,
						    EncodecConfig,
						)
						from .feature_extraction_encodec import EncodecFeatureExtractor

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_encodec import (
												    ENCODEC_PRETRAINED_MODEL_ARCHIVE_LIST,
												    EncodecModel,
												    EncodecPreTrainedModel,
												)

else:
						import sys

						lowerCAmelCase					:    Dict           = _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)








'''simple docstring'''


import tempfile
import unittest

from make_student import create_student_by_copying_alternating_layers

from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch


UpperCAmelCase_						:  List[Any]				  =						'sshleifer/bart-tiny-random'
UpperCAmelCase_						:  Tuple				  =						'patrickvonplaten/t5-tiny-random'





@require_torch
class        lowercase__    (		unittest.TestCase   ):





							'''simple docstring'''


							@cached_property
							def UpperCAmelCase_      (       self    ):
											return AutoConfig.from_pretrained(__snake_case    )






							def UpperCAmelCase_      (       self    ):
											_SCREAMING_SNAKE_CASE						,			*_SCREAMING_SNAKE_CASE					:			int							= create_student_by_copying_alternating_layers(__snake_case       ,   tempfile.mkdtemp()       ,   e=1       ,   d=1    )
											self.assertEqual(student.config.num_hidden_layers       ,   1    )






							def UpperCAmelCase_      (       self    ):
											_SCREAMING_SNAKE_CASE						,			*_SCREAMING_SNAKE_CASE					:			int							= create_student_by_copying_alternating_layers(__snake_case       ,   tempfile.mkdtemp()       ,   e=1       ,   d=__snake_case    )






							def UpperCAmelCase_      (       self    ):
											_SCREAMING_SNAKE_CASE						,			*_SCREAMING_SNAKE_CASE					:			str							= create_student_by_copying_alternating_layers(__snake_case       ,   tempfile.mkdtemp()       ,   e=1       ,   d=__snake_case    )
											self.assertEqual(student.config.encoder_layers       ,   1    )
											self.assertEqual(student.config.decoder_layers       ,   self.teacher_config.encoder_layers    )






							def UpperCAmelCase_      (       self    ):
											_SCREAMING_SNAKE_CASE						,			*_SCREAMING_SNAKE_CASE					:			Union[str, Any]							= create_student_by_copying_alternating_layers(__snake_case       ,   tempfile.mkdtemp()       ,   e=1       ,   d=1    )
											self.assertEqual(student.config.encoder_layers       ,   1    )
											self.assertEqual(student.config.decoder_layers       ,   1    )






							def UpperCAmelCase_      (       self    ):
											with self.assertRaises(__snake_case    ):
															create_student_by_copying_alternating_layers(__snake_case       ,   tempfile.mkdtemp()       ,   e=__snake_case       ,   d=__snake_case    )




